Automatic Search for Photoacoustic Marker Using Automated Transrectal Ultrasound

TL;DR

This study develops an automatic method to locate photoacoustic markers in transrectal ultrasound images during prostate surgery, improving registration accuracy and reducing manual effort.

Contribution

It introduces the first automatic search algorithm for PA markers using a transrectal ultrasound robot, comparing three algorithms in simulation and ex vivo tests.

Findings

Weighted Average algorithm achieved 0.53° error after 9 acquisitions

Ternary Search achieved 0.29° error after 28 acquisitions

Golden Section Search achieved 0.48° error after 28 acquisitions

Abstract

Real-time transrectal ultrasound (TRUS) image guidance during robot-assisted laparoscopic radical prostatectomy has the potential to enhance surgery outcomes. Whether conventional or photoacoustic TRUS is used, the robotic system and the TRUS must be registered to each other. Accurate registration can be performed using photoacoustic (PA markers). However, this requires a manual search by an assistant [19]. This paper introduces the first automatic search for PA markers using a transrectal ultrasound robot. This effectively reduces the challenges associated with the da Vinci-TRUS registration. This paper investigated the performance of three search algorithms in simulation and experiment: Weighted Average (WA), Golden Section Search (GSS), and Ternary Search (TS). For validation, a surgical prostate scenario was mimicked and various ex vivo tissues were tested. As a result, the WA algorithm can achieve 0.53 degree average error after 9 data acquisitions, while the TS and GSS algorithm can achieve 0.29 degree and 0.48 degree average errors after 28 data acquisitions.